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Hotspots within a global biodiversity hotspot - areas of endemism are associated with high mountain ranges

Published on Dec 1, 2018in Scientific Reports4.01
· DOI :10.1038/s41598-018-28504-9
Jalil Noroozi9
Estimated H-index: 9
(University of Vienna),
Amir Talebi1
Estimated H-index: 1
(UT: University of Tehran)
+ 3 AuthorsGerald M. Schneeweiss35
Estimated H-index: 35
(University of Vienna)
Abstract
Conservation biology aims at identifying areas of rich biodiversity. Currently recognized global biodiversity hotspots are spatially too coarse for conservation management and identification of hotspots at a finer scale is needed. This might be achieved by identification of areas of endemism. Here, we identify areas of endemism in Iran, a major component of the Irano-Anatolian biodiversity hotspot, and address their ecological correlates. Using the extremely diverse sunflower family (Asteraceae) as our model system, five consensus areas of endemism were identified using the approach of endemicity analysis. Both endemic richness and degree of endemicity were positively related to topographic complexity and elevational range. The proportion of endemic taxa at a certain elevation (percent endemism) was not congruent with the proportion of total surface area at this elevation, but was higher in mountain ranges. While the distribution of endemic richness (i.e., number of endemic taxa) along an elevational gradient was hump-shaped peaking at mid-elevations, the percentage of endemism gradually increased with elevation. Patterns of endemic richness as well as areas of endemism identify mountain ranges as main centres of endemism, which is likely due to high environmental heterogeneity and strong geographic isolation among and within mountain ranges. The herein identified areas can form the basis for defining areas with conservation priority in this global biodiversity hotspot.
  • References (94)
  • Citations (8)
References94
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Cited By8
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#1Shengwei Wang (CAS: Chinese Academy of Sciences)H-Index: 1
#2Biyansa H. Boru (CAS: Chinese Academy of Sciences)H-Index: 1
Last.Qing-Feng Wang (CAS: Chinese Academy of Sciences)H-Index: 18
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#1Mohammad Bagher Erfanian (FUM: Ferdowsi University of Mashhad)
#2Hamid Ejtehadi (FUM: Ferdowsi University of Mashhad)H-Index: 3
Last.Mohammad Firouz‐Jahantigh (FUM: Ferdowsi University of Mashhad)
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#1Elaheh Parvizi (UT: University of Tehran)H-Index: 2
#2Alireza Keikhosravi (HSU: Hakim Sabzevari University)H-Index: 3
Last.Christoph D. Schubart (University of Regensburg)H-Index: 27
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